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- Delft University of Technology (TU Delft); Delft
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- Delft University of Technology (TU Delft); yesterday published
- Eindhoven University of Technology (TU/e)
- Eindhoven University of Technology (TU/e); Eindhoven
- Radboud University; 3 Oct ’25 published
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- University of Amsterdam (UvA); today published
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input signals. Your goal will be to explore material systems that host novel types of correlated electron ground states as well as pushing forwards the limit of the implementation of brain-inspired
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to creativity in AVT in different translation modalities, define whether user attention and preference is linked to creativity, and gather data on how errors affect user attention. You will use a mixed method
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signal processing, with a strong emphasis on quantitative methods. The DAF Technology Lab is a university facility consisting of office space, three research cabins and two CAVE (Cave Automatic Virtual
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, define whether user attention and preference is linked to creativity, and gather data on how errors affect user attention. You will use a mixed method approach to analyse the impact that technology has
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. One challenge here is to understand and control the dynamic response of the system for complex input signals. Your goal will be to explore material systems that host novel types of correlated electron
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to investigate structure-property relationships of the synthesized materials both from fundamental point of view and for industrial application in CO2 separation and storage processes; You are open to
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, socio-spatial inequalities and real estate applying quantitative, qualitative and mixed research methods. Our ideal candidate should have: A PhD-degree (or nearly finished) in the field of economic
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to utilise material platforms that exhibit multiwell behaviour. One challenge here is to understand and control the dynamic response of the system for complex input signals. Your goal will be
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have skills in solid-state chemistry and materials characterisation; You have a keen interest to investigate structure-property relationships of the synthesized materials both from fundamental point
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assess relevant climate change metrics or indicators for the above point; design AI pipelines that fuse EO data and climate scenarios/projections (e.g., CMIP, CORDEX, DestinE Digital Twin for Climate